Skip to main content
Log in

Curve interpolation with constrained length

Interpolation mit Kurven beschränkter Länge

  • Published:
Computing Aims and scope Submit manuscript

Abstract

We consider the problem of finding a curve which interpolates at given points such that (approximately) the length of the curve between each two subsequent interpolation points is equal to some given number. We only consider the functional case. We give an algorithm which yields an interpolating cubic polynomial spline. In case the data is taken from a (smooth enough) function this spline function converges at least quadratically in the mesh size to the original one. If the mesh is ‘regular enough’ it is even third order accurate. We also given an extension to the bivariate case. For the univariate case it will be shown that the length on each interval of this constructed spline at most differs quadratically in the mesh size from the actual lengths. Assuming regularity on the partition this estimate can also be improved by one order.

Zusammenfassung

Wird befassen uns mit dem Problem, eine Kurve zu bestimmen, die in gegebenen Punkten interpoliert und deren Länge zwischen zwei aufeinanderfolgenden Punkten (näherungsweise) gleich einer vorgegebenen Zahl ist. Wir betrachten dabei den Fall, daß die Kurve durch eine Funktion gegeben ist. Es wird ein Algorithmus zur Berechnung eines interpolierenden kubischen Splines vorgestellt. Für Interpolationsdaten von einer (genügend) glatten Funktion ist die Konvergenz der Spline-Funktion mindestens quadratisch in der Maschenweite. Bei (genügend) regulärem Gitter tritt sogar eine Konvergenz der Ordnung drei auf. Wir betrachten ferner den zweidimensionalen Fall. Für den eindimensionalen Fall zeigen wir, daß auch der Fehler des berechneten Splines in der vorgeschriebenen Länge zwischen den Gitterpunkten quadratisch mit der Maschenweite abnimmt. Auch hier erreicht man bei regulärem Gitter eine Erhöhung der Konvergenzordnung um eins.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Carnicer Álvarez, J. M.: Convexity preserving interpolation. PhD thesis, University of Zaragoza, 1991.

  2. Barnhill, R. E., Farin, G., Fayand, L., Hagen, H.: Twist curvatures and surface interrogations Comput. Aided Des.20, 341–346 (1988).

    Article  Google Scholar 

  3. Beatson, R. K., Ziegler, Z.: Monotonicity preserving surface interpolation. SIAM J. Numer. Anal.22, 401–411 (1985).

    Article  Google Scholar 

  4. Carlson, R. E., Fritsch, F. N.: An algorithm for monotone piecewise bicubic interpolation. SIAM J. Numer. Anal.26, 230–238 (1989).

    Article  Google Scholar 

  5. Carlson, R. E., Fritsch, F. N.: Monotone piecewise bicubic interpolation. SIAM J. Numer. Anal.22, 386–401 (1989).

    Article  Google Scholar 

  6. Costantini, P.: Co-monotone interpolating spline of arbitrary degree: a local approach. J. Sci. Stat. Comp.8, 1026–1034 (1987).

    Article  Google Scholar 

  7. Costantini, P.: An algorithm for computing shape preserving interpolating splines of arbitrary degree. J. Comput. Appl. Math.223, 89–136 (1988).

    Article  Google Scholar 

  8. Costantini, P., Fontanella, F.: Shape-preserving bivariate interpolation, SIAM J. Numer. Anal.27, 488–506 (1990).

    Article  Google Scholar 

  9. Dahmen, W., Micchelli, C. A.: Convexity of multivariate Bernstein polynomials and box spline surfaces. Studia Sci. Math. Hung.23, 265–287 (1988).

    Google Scholar 

  10. Davis, P. J.: Interoolation and approximation. New York-Toronto: Blaisdell 1963.

    Google Scholar 

  11. Dodd, S. L., McAllister, D. F., Roulier, J. A.: Shape-preserving spline interpolation for specifying bivariate functions on grids. IEEE Comput. Graph. Appl.3, 70–79 (1983).

    Google Scholar 

  12. Edelman, A. Micchelli, C. A.: Admissible slopes for monotone and convex interpolation. Numer. Math.51, 441–458 (1987).

    Article  Google Scholar 

  13. Eisenstat, S. C., Jackson, K. R., Lewis, J. W.: The order of monotone piecewise cubic interpolation. SIAM J. Numer. Anal.22, 1220–1237 (1985).

    Article  Google Scholar 

  14. Fritsch, F. N., Carlson, R. E.: Monotone piecewise cubic interpolation. SIAM J. Numer. Anal.17, 238–246 (1980).

    Article  Google Scholar 

  15. Mulansky, B.: Interpolation of scattered data by a bivariate convex function. I: Piecewise linearC 0-interpolation. Memorandum no. 858, University of Twente, 1990.

  16. Mulansky, B.: A remark on the convexity of piecewise polynomial functions on triangulations. Memorandum no. 857, University of Twente, 1990.

  17. Passow, E. Roulier, J. A.: Shape preserving spline interpolation. In: Lorentz, G. G. (ed.) Approximation theory II, pp. 503–507. New York: Academic Press 1976.

    Google Scholar 

  18. Schultz, M. H.: Spline analysis. Automatic computation. Englewood Cliffs: Prentice Hall 1973.

    Google Scholar 

  19. Scott, D. S.: The complexity of interpolating given data in three-space with a convex function in two variables. J. Approx. Theory42, 52–63 (1984).

    Article  Google Scholar 

  20. Utreras, F. I.: Constrained surface construction. In: Schumaker, L. L., Chui, C. K., Utreras, F. I. (eds.) Topics in multivariate approximation, pp. 233–254. New York: Academic Press 1987.

    Google Scholar 

  21. Yamaguchi, F.: Curves and surfaces in computer aided geometric design. Berlin Heidelberg New York Tokyo: Springer 1988.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

van Damme, K., Wang, R.H. Curve interpolation with constrained length. Computing 54, 69–81 (1995). https://doi.org/10.1007/BF02238080

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02238080

1991 Mathematics Subject Classification

Key words

Navigation